Do Historic Landscape Images Predict Tourists’ Spatio-Temporal Behavior at Heritage Sites? A Case Study of West Lake in Hangzhou, China

Qiqi Liu, Xiaolan Tang () and Ka Li
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Qiqi Liu: College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
Xiaolan Tang: College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
Ka Li: College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China

Land, 2022, vol. 11, issue 10, 1-20

Abstract: Rich in history and culture, heritage sites often evoke stirring emotions and memories. We analyzed historical poetry using grounded theory and high-frequency word and semantic analysis to construct historic landscape images (HLIs) of the West Lake UNESCO World Heritage Site in Hangzhou, China. GPS trajectory data were used to identify hot and cold tourist spots and understand the site’s intra-attraction tourist behaviors (IATBs). Finally, we analyzed the HLI–IATB relationship. We found that the tourist distribution was uneven, and different attractions had different visitor behaviors. Our findings should inform future heritage site management—and neighboring cities—about the benefits of using HLIs to predict attraction visitors’ behaviors and leveraging those insights to optimize multiple-attraction sites proportionally. Such projections can provide new perspectives for heritage studies, landscape planning, and tourism image-making.

Keywords: historic landscape images; intra-attraction tourist behaviors; GPS; big data; world heritage sites (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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